Name
Title | ||
|---|---|---|
Finite/fixed-time synchronization of delayed memristive reaction-diffusion neural networks |
Abstract | ||
|---|---|---|
This paper is concerned with the finite/fixed-time synchronization (FFTS) problems of two delayed memristive reaction–diffusion neural networks (MRDNNs). By designing appropriate state feedback controllers, utilizing the Lyapunov function method and inequality techniques, several sufficient criteria are derived to guarantee the FFTS of the drive-response MRDNNs. Taking into account both the influences of time and space, the model, described as a state-dependent switching system here, is more complex and closer to practical applications than those in the existing results. Finally, an example is presented to substantiate the effectiveness of the theoretical results. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.neucom.2019.06.092 | Neurocomputing |
Keywords | Field | DocType |
Finite/fixed-time synchronization,Reaction–diffusion,Memristive neural network,State feedback controller | Fixed time,Lyapunov function,Synchronization,Pattern recognition,Control theory,Spacetime,Time synchronization,Artificial intelligence,Artificial neural network,Reaction–diffusion system,Mathematics | Journal |
Volume | ISSN | Citations |
375 | 0925-2312 | 3 |
PageRank | References | Authors |
0.36 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shiqin Wang | 1 | 15 | 3.18 |
| Zhenyuan Guo | 2 | 89 | 8.75 |
| Shiping Wen | 3 | 1231 | 72.34 |
| Tingwen Huang | 4 | 5684 | 310.24 |